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System Development & Application
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214-221

Machine solving method for math word problem based on semantic understanding enhancement

Jian Pengpeng1
Yan Ming1
Wang Yanli2
1. School of Information Engineering, North China University of Water Resources & Electric Power, Zhengzhou 450046, China
2. Henan University of Economics & Law, Zhengzhou 450016, China

Abstract

Since the existing machine solving methods of math word problems cannot adaptively understand the text of the problem with changing semantics, and have a limit in the improvement of solving accuracy, this paper proposed a machine solving method based on semantic understanding enhancement. Firstly, this method designed a semantically enhanced pre-training language model SeBERT to accurately understand the topic through a multi-granularity knowledge modeling strategy and continuous semantic integration strategy. Secondly, this method constructed the solution model SeBERT-PT, which adopted the solution structure of language model-pool-tree to effectively improve the semantic understanding deviation of word problems and the accuracy of understanding problems. Finally, it introduced a confidence-based judgment mechanism to directly determine the failure of solving untrustworthy predictions, ensure the accuracy of the solution, and improve the training efficiency of solving models. The experimental results show that the accuracy results on Chinese and English datasets are 85.7% and 77.9% respectively, which is superior to other baseline methods, especially on problems involving complex semantic understanding and logical reasoning. It has proved the effectiveness of the method in improving the accuracy of solving math word problems and demonstrates its wide applicability in cross-language environments.

Foundation Support

国家自然科学基金资助项目(62107014)
河南省青年人才托举工程项目(2023HYTP046)
河南省重点研发与推广专项资助项目(232102320155)
河南省高等教育教学改革研究与实践重大项目(2021SJGLX017)
新工科背景下现代产业学院信创人才培养模式研究与实践(2024SJGLX0108)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.06.0208
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 1
Section: System Development & Application
Pages: 214-221
Serial Number: 1001-3695(2025)01-029-0214-08

Publish History

[2025-01-05] Printed Article

Cite This Article

菅朋朋, 闫鸣, 王彦丽. 基于语义理解增强的数学应用题机器解答方法 [J]. 计算机应用研究, 2025, 42 (1): 214-221. (Jian Pengpeng, Yan Ming, Wang Yanli. Machine solving method for math word problem based on semantic understanding enhancement [J]. Application Research of Computers, 2025, 42 (1): 214-221. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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